Plasmon losses due to electron-phonon scattering: the case of graphene encapsulated in hexagonal Boron Nitride

Graphene sheets encapsulated between hexagonal Boron Nitride (hBN) slabs display superb electronic properties due to very limited scattering from extrinsic disorder sources such as Coulomb impurities and corrugations. Such samples are therefore expected to be ideal platforms for highly-tunable low-loss plasmonics in a wide spectral range. In this Article we present a theory of collective electron density oscillations in a graphene sheet encapsulated between two hBN semi-infinite slabs (hBN/G/hBN). Graphene plasmons hybridize with hBN optical phonons forming hybrid plasmon-phonon (HPP) modes. We focus on scattering of these modes against graphene's acoustic phonons and hBN optical phonons, two sources of scattering that are expected to play a key role in hBN/G/hBN stacks. We find that at room temperature the scattering against graphene's acoustic phonons is the dominant limiting factor for hBN/G/hBN stacks, yielding theoretical inverse damping ratios of hybrid plasmon-phonon modes of the order of $50$-$60$, with a weak dependence on carrier density and a strong dependence on illumination frequency. We confirm that the plasmon lifetime is not directly correlated with the mobility: in fact, it can be anti-correlated.Comment: 14 pages, 4 figure

Nonlocal Thermoelectricity in a S-TI-S Junction in Contact with a N-Metal Probe: Evidence for Helical Edge States

We consider a Josephson junction hosting a Kramers pair of helical edge states of a quantum spin Hall bar in contact with a normal-metal probe. In this hybrid system, the orbital phase induced by a small magnetic field threading the junction known as Doppler shift (DS), combines with the conventional Josephson phase difference and originates an effect akin to a Zeeman field in the spectrum. As a consequence, when a temperature bias is applied to the superconducting terminals, a thermoelectric current is established in the normal probe. We argue that this purely non-local thermoelectric effect is a unique signature of the helical nature of the edge states coupled to superconducting leads and it can constitute a useful tool for probing the helical nature of the edge states in systems where the Hall bar configuration is difficult to achieve. We fully characterize thermoelectric response and performance of this hybrid junction in a wide range of parameters, demonstrating that the external magnetic flux inducing the DS can be used as a knob to control the thermoelectric response and the heat flow in a novel device based on topological junctions

Nonlocal thermoelectricity in a topological Andreev interferometer

We discuss the phase dependent nonlocal thermoelectric effect in a topological Josephson junction in contact with a normal-metal probe. We show that, due to the helical nature of topological edge states, nonlocal thermoelectricity is generated by a purely Andreev interferometric mechanism. This response can be tuned by imposing a Josephson phase difference, through the application of a dissipationless current between the two superconductors, even without the need of applying an external magnetic field. We discuss in detail the origin of this effect and we provide also a realistic estimation of the nonlocal Seebeck coefficient that results of the order of few $\mu V/K$

Automating Mitigation of Amplification Attacks in NFV Services

The combination of virtualization techniques with capillary computing and storage resources allows the instantiation of Virtual Network Functions throughout the network infrastructure, which brings more agility in the development and operation of network services. Beside forwarding and routing, this can be also used for additional functions, e.g., for security purposes. In this paper, we present a framework to systematically create security analytics for virtualized network services, specifically targeting the detection of cyber-attacks. Our framework largely automates the deployment of security sidecars into existing service templates and their interconnection to an external analytics platform. Notably, it leverages code augmentation techniques to dynamically inject and remove inspection probes without affecting service operation. We describe the implementation of a use case for the detection of DNS amplification attacks in virtualized 5G networks, and provide extensive evaluation of our innovative inspection and detection mechanisms. Our results demonstrate better efficiency with respect to existing network monitoring tools in terms of CPU usage, as well as good accuracy in detecting attacks even with variable traffic patterns